[R] Automating R for Hypothesis Testing

meredith mmballar at mtu.edu
Wed May 9 13:46:21 CEST 2012


dput:  http://r.789695.n4.nabble.com/file/n4620188/milwaukeephos.csv
milwaukeephos.csv 

# Feb-march
> modelH_febmarch<-lm(llfeb_march~lffeb_march)
>modelHa_febmarch<-lm(llfeb_march~X1feb_mar+lffeb_march)
> anova(modelHa_febmarch)
> coefficients(modelH_febmarch)
(Intercept) lffeb_march 
  -2.429890    1.172821 
> coefficients(modelHa_febmarch)
(Intercept)   X1feb_mar lffeb_march 
 -2.8957776  -0.5272793   1.3016303 
> bres_fm<-matrix(c(-2.429890,0,1.172821),nrow=3)
> bunres_fm<-matrix(c(-2.8957776,-0.5272793,1.3016303),nrow=3)
>bfm<-t(bunres_fm-bres_fm)
> fmvect<-seq(1,1,length=34)
> X1a_febmar<-seq(0,0,length=9) # dummy variable step 1
> X1b_febmar<-seq(1,1,length=25) # dummy variable step 2
> X1feb_mar<-c(X1a_febmar,X1b_febmar) #dummy variable creation
# Test Stat Equation for Chisq
> fmxx<-cbind(fmvect,X1feb_mar,lffeb_march)
> tfmx<-t(fmxx)
> xcom_fm<-(tfmx %*% fmxx)
> xinv_fm<-ginv(xcom_fm)
> var_fm<-xinv_fm*0.307
> chi_fm<-bfm %*% var_fm %*% (bunres_fm-bres_fm)
> chi_fm # chisq value for recording
if less than CV move onto to slope modification
> modelH2_febmarch<-lm(llfeb_march~X3feb_march)
> modelH2a_febmarch<-lm(llfeb_march~X3feb_march+X4feb_march)
> anova(modelH2a_febmarch)
> coefficients(modelH2_febmarch) # get coefficients to make beta vectors for
> test
(Intercept) X3feb_march 
   5.342130    1.172821 
> coefficients(modelH2a_febmarch)
(Intercept) X3feb_march X4feb_march 
  5.2936263   1.0353752   0.2407557 
# Test Stat
> bsres_fm<-matrix(c(5.342130,1.172821,0),nrow=3)
> bsunres_fm<-matrix(c(5.2936263,1.0353752,0.2407557),nrow=3)
> bsfm<-t(bsunres_fm-bsres_fm)
> #X matrix
> fmxs<-cbind(fmvect,X3feb_march,X4feb_march)
> tfmxs<-t(fmxs)
> xcoms_fm<-(tfmxs %*% fmxs)
> xinvs_fm<-ginv(xcoms_fm)
> var_fms<-xinvs_fm*0.341
> chi_fms<-bsfm %*% var_fms %*% (bsunres_fm-bsres_fm)
> chi_fms
# Record Chisq value

Does this help?
Here lffeb_march is the combination of Feb and March log flows
and llfeb_march is the combination of Feb and March log loads
X3: lffeb_march-mean(feb_march)
X4: X1*X3

Thanks

Rui Barradas wrote
> 
> Hello,
> 
> I'm not at all sure if I understand your problem. Does this describe it?
> 
> 
> test first model for months 1 and 2
> if test statistic less than critical value{
> 	test second model for months 1 and 2
> 	print results of the first and second tests? just one of them?
> }
> move on to months 2 and 3
> etc, until months 12 and 1
> 
> 
> Please post example data using dput(dataset).
> Just copy it's output and paste it in your post.
> 
> And example code, what you're already doing.
> (Possibly simplified)
> 
> Rui Barradas
> 
> 
> meredith wrote
>> 
>> R Users-
>>   I have been trying to automate a manual code that I have developed for
>> calling in a .csv file, isolating certain rows and columns that
>> correspond to specified months:
>> something to the effect
>> i=name.csv
>> N=length(i$month)
>> iphos1=0
>> iphos2=0
>> isphos3=0
>> for i=1,N
>>  if month=1
>>     iphos1=iphos+1
>>     iphos1(iphos1)=i
>> 
>> an so on to call out the months into there own arrays (unless there is a
>> way I can wrap it into the next automation)
>> 
>> Next: I would like to run a simple linear regression combining each of
>> the months 1 by 1:
>> for instance I want to run a regression on a combined model from months 1
>> and 2 and a dummy model for 1 and 2, compare them using a Chi-sq
>> distribution, if Chi-sq is less than the Critical value, we accept and go
>> on to test another set of models with both 1 and 2. If it rejects, then
>> we proceed to months 2 and 3.  If we move on to the second set on months
>> 1 and 2, and the critical value is accepted, I want to print an accept or
>> reject and move on to months 2 and 3, until finally comparing months 12-1
>> at the end.
>> Is there a way to loop or automate this in R?
>> 
>> Thanks
>> Meredith
>> 
> 

Rui Barradas wrote
> 
> Hello,
> 
> I'm not at all sure if I understand your problem. Does this describe it?
> 
> 
> test first model for months 1 and 2
> if test statistic less than critical value{
> 	test second model for months 1 and 2
> 	print results of the first and second tests? just one of them?
> }
> move on to months 2 and 3
> etc, until months 12 and 1
> 
> 
> Please post example data using dput(dataset).
> Just copy it's output and paste it in your post.
> 
> And example code, what you're already doing.
> (Possibly simplified)
> 
> Rui Barradas
> 
> 
> meredith wrote
>> 
>> R Users-
>>   I have been trying to automate a manual code that I have developed for
>> calling in a .csv file, isolating certain rows and columns that
>> correspond to specified months:
>> something to the effect
>> i=name.csv
>> N=length(i$month)
>> iphos1=0
>> iphos2=0
>> isphos3=0
>> for i=1,N
>>  if month=1
>>     iphos1=iphos+1
>>     iphos1(iphos1)=i
>> 
>> an so on to call out the months into there own arrays (unless there is a
>> way I can wrap it into the next automation)
>> 
>> Next: I would like to run a simple linear regression combining each of
>> the months 1 by 1:
>> for instance I want to run a regression on a combined model from months 1
>> and 2 and a dummy model for 1 and 2, compare them using a Chi-sq
>> distribution, if Chi-sq is less than the Critical value, we accept and go
>> on to test another set of models with both 1 and 2. If it rejects, then
>> we proceed to months 2 and 3.  If we move on to the second set on months
>> 1 and 2, and the critical value is accepted, I want to print an accept or
>> reject and move on to months 2 and 3, until finally comparing months 12-1
>> at the end.
>> Is there a way to loop or automate this in R?
>> 
>> Thanks
>> Meredith
>> 
> 


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